Fractional reserve banking isn't a thing anymore.
2,778 karma · joined June 15, 2016
Why? I really don’t think it’s a good idea to try to measure something as complex and multi-faceted as the evolution of an economy with a scalar.
The code it generates contains subtle bugs (e.g changing the minus to a plus in recursive factorial)
Cash is a liability of the central bank, yep. Destroying it removes a liability from the bank's balance sheet, increasing their equity. As others have noted, destroying cash is equivalent to returning money to an arm of government.
As you say, if people destroyed cash on a regular basis, it would be deflationary: the central bank would respond by lowering interest rates. When the increased equity was eventually booked as profit, it would go back to the government, who would (presumably) spend it.
Both the lower rates and the increased spending are inflationary, so in the long run we might expect that the system would balance itself out.
I don't think there's any reason to believe that employee scores (out of 100, say) should be normally distributed.
The weirdness of the axiom of choice only really comes through when you consider bigger and bigger collections of sets.
For example:
- sets indexed by the natural numbers: S_1, S_2, ... It seems totally reasonable that you should be able to make a new set by picking something from the first set, something from the second set, etc
- sets indexed by continuous time (i.e. real numbers). Here it's a bit less 'obvious'. If I have sets S_t for _every_ time t > 0, can I really make choices 'fast' enough? What if the sets are so unstructured that I'm forced to stop and look at each set in turn to make my choice?
- sets indexed by the power set of the real numbers. If you weren't convinced that I'd struggle to pick elements of S_t for all t > 0, what if I had to make a choice for every _possible combination_ of real numbers, infinite or otherwise?
I feel like the last example demonstrates how powerful the full axiom of choice actually is.
NB - I'm a dilettante rather than an actual logician, so there may be mathematical inaccuracies here.
- The 'problem' with B-T may be related to our notion of "space" (i.e. point-set topology) rather than any issues with the axiom of choice
- Most practical uses of the axiom of choice could get by with the axiom of countable choice, under which B-T doesn't hold
- Mathematics need not directly model the 'real' world or match our physical intuition
[0] https://mathoverflow.net/questions/260057/axiom-of-choice-ba...
Not that they’d necessarily veto, but the politics aren’t clear-cut.
But I guess the point is that almost no-one does this. I would guess that if someone tried to formally verify every published paper out there (or even every textbook), they would uncover a large number of gaps. Very few of those gaps would be unfixable, and very few results would turn out to be incorrect, but the possibility exists.
There's also quite a large body of (academic) work applying topological methods to robotics. Robots have complex configuration spaces and apparently topological methods can help us understand those spaces.
As others have pointed out, the voting system means you only see the best of the comments. And even then when HN strays "off topic" (i.e. away from science and tech) the commentary is far less on point.
And don't get me started on the "middle-brow dismissal"...
The simplest thing you can do is chase returns. Maybe you do that by looking at assets that have yielded large returns over the past N days. If you do so using total returns (i.e. price appreciation plus dividends, coupons, or whatever) that will bias you towards high yield bonds and high-risk equities. History says that’s honestly not a bad strategy.
If you decide you want to be less prone to buying high-yield assets that usually pay out but that could crumble at a moment’s notice, the next-simplest thing you can do is ask whether an asset has produced a good return relative to its long-term history. There are all sorts of reasons this could happen: maybe it’s a stock in a sector that recently became popular. Or maybe interest rates are falling and it’s a long duration bond.
In any case, it’s not obviously a bad idea to buy assets with recent good performance. “Hop on the bandwagon” works ok as an investment thesis IMO.
The key is that you operate in as many markets as possible and let diversification do the hard work for you. If you eke out a small edge that works across markets, on average you’ll do ok.
That’s my 2c on the systematic technical trading mentality. You don’t need to swallow it wholesale, but I don’t it’s fair to characterise texhnicL traders as a bunch of swivel-eyed loons either.
Then the diffusive part says
du(x, t)/dt = \nabla_x u(x, t).
The \nabla term is the laplacian: a multivariate form of the second derivative.
The equation says that a short time from now, u(x, t) will change in proportion to the average value of u, calculated over a small ball surrounding the point x, minus the value of u at the point x itself.
If there's less "stuff" in the points that neighbour x than at x itself, the function will decrease over time. Similarly if there's more stuff at the neighbours of x, u(x, t) will increase. This is the basis of diffusive behaviour.
(Edit: I think the equation in the article is wrong, unless I've misunderstood something: they have a delta (first derivative) when they should have a nabla (laplacian))
I think of it in terms of neck muscles. If your car is accelerating at a constant rate, you feel that as a force pushing your head back. Your neck muscles activate to compensate and keep your head still.
If the acceleration changes suddenly and aggressively (i.e. high jerk), so does the force on your neck. So either your neck muscles react quickly to counteract the new force, or your head bounces around.
Higher order derivatives also matter, but mostly inasfar as they act on the acceleration (and hence force) that you feel.
Suppose I want to buy something online using crypto. I buy up $X worth and transfer it to the vendor. They transfer whatever it was that they bought, but they immediately redeem the bitcoin for $X, give or take a small amount from market moves.
There’s no net demand for crypto here, and the increase in crypto price from my purchase will roughly be offset by their sale.
I think the only way to explain crypto prices is through buyers hoping that they’ll be used as a store of value. I don’t agree with that, but that’s a different story.
Not great phrasing I agree but the information is there.
Most comments were splitting hairs on what _exactly_ the Dunning-Kruger effect was, plus some general nerd-sniping on how the original article was off base.
IMO it was something that fell flat on its own rather than something that needed a lengthy refutation, but I can understand that sometimes these things get under your skin.
Machine learning contains ANNs as a sub-discipline. Other non-ANN topics in ML include ensembled trees, Gaussian processes, and sampling theory.
Even if one buys into the idea that human behaviour is a 'function' of sensory and environmental 'inputs', that's a long way from showing a neural net a million different texts and asking it to generalise.